Title :
A novel technique for tracking time-varying minimum and its applications
Author :
Zhao, Y. ; Swamy, M.N.S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada
Abstract :
A technique for tracking the time-varying minimum of a time-dependent function is proposed. It ensures the tracking process converge exponentially. It also enables the tracking to move from the minimum at one instant of time to the minimum at the next instant of time, without any error. Examples are given to show that this technique is effective for tracking the time-varying minimum. Application of this technique to on-line continuous system identification, on-line neural network learning, etc. gives rise to improved results
Keywords :
Newton method; convergence of numerical methods; feedforward neural nets; identification; learning (artificial intelligence); optimisation; time-varying systems; tracking; Newton technique; exponential convergence rate; feed forward neural network; on-line continuous system identification; on-line neural network learning; optimization; time-dependent function; time-varying minimum tracking; Analog circuits; Application software; Continuous time systems; Control systems; Counting circuits; Electronic circuits; Equations; Neural networks; Signal processing; System identification;
Conference_Titel :
Electrical and Computer Engineering, 1998. IEEE Canadian Conference on
Conference_Location :
Waterloo, Ont.
Print_ISBN :
0-7803-4314-X
DOI :
10.1109/CCECE.1998.685646
